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Learning effective representations helps characterize the structure and dynamics of equity markets from financial data with a low signal-to-noise ratio. Black-box deep models can capture complex patterns but may overfit sample noise and lack explicit economic structure. Meanwhile, classic linear financial models provid...
This work introduces AlphaOpsBench, which evaluates end-to-end operationalization from source-grounded economic hypotheses to auditable executable programs over 581 source-preserving strategy records and a lifecycle-scale Polymarket dataset, and separates strategy fidelity, behavioral validity, historical executability...
This work describes the data model, collection pipeline, and consistency mechanisms that make the datasets reproducible and extensible of decentralized prediction markets reproducible and extensible, and demonstrates its utility for multiple communities through NBA outcome calibration for sport traders, CPI expectation...
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